Multi-UAV Coverage Path Assignment Algorithm Considering Flight Time and Energy Consumption

Abstract

Coverage path planning is an important research direction for unmanned aerial vehicles (UAV), which are primarily used in ground search or mapping scenarios. Although there have been a large number of studies on UAV coverage path planning, there are still some problems in the cooperative work of multi-UAV in complex environments under the constraints of energy consumption and work efficiency requirements of UAV. To solve unnecessary energy loss when multiple UAVs jointly execute complex area coverage tasks and improve the overall work efficiency of the UAV swarm. In this study, we simulated the situation of multiple UAVs performing the mission of area coverage under the constraints of the corresponding energy consumption in a work environment with no-fly zones. We propose the use of multiple UAV base stations to provide takeoff and landing services for UAVs that perform missions. We proposed two algorithms. One is the multi-base station multi-UAV cooperative coverage path planning algorithm with flexible obstacle avoidance ability (MBS-MUCCPPAFOA), which performs coverage route planning from an entire area using multiple base stations to perform multi-UAV area coverage tasks. The other algorithm is a multi-UAV cooperative coverage path planning algorithm with flexible obstacle avoidance capability based on area segmentation (MUAV-CCPPAFOA-AS), which divides the entire work area and performs coverage path planning for each sub-area to perform multi-UAV area coverage tasks. We compared the proposed algorithm with the common scanning coverage path planning algorithm, and proved the robustness of the proposed MBS-MUCCPPAFOA and MUAV-CCPPAFOA-AS algorithms.

Keywords

• Cooperative unmanned aerial vehicle teams
• coverage path planning problems
• CPP
• path planning
• multiple traveling salesmen problems
• MTSP